Frequency of Visual Fields Needed to Detect Glaucoma Progression: A Computer Simulation Using Linear Mixed Effects Model.

PRCIS: Irregular visual field test frequency at relatively short intervals initially and longer intervals later on in the disease provided acceptable results in detecting glaucoma progression. PURPOSE: It is challenging to maintain a balance between the frequency of visual field testing and the long-term costs that may result from insufficient treatment of glaucoma patients. This study aims to simulate real-world circumstances of visual field data to determine the optimum follow-up scheme for the timely detection of glaucoma progression using a linear mixed effects model (LMM). MATERIALS AND METHODS: An LMM with random intercept and slope was used to simulate the series of mean deviation sensitivities over time. A cohort study including 277 glaucoma eyes that were followed for 9.0±1.2 years was used to derive residuals. Data were generated from patients with early-stage glaucoma having various regular and irregular follow-up scenarios and different rates of visual field loss. For each condition, 10,000 series of eyes were simulated, and one confirmatory test was conducted to identify progression. RESULTS: By doing one confirmatory test, the percentage of incorrect progression detection decreased considerably. The time to detect progression was shorter for eyes with an evenly spaced 4-monthly schedule, particularly in the first 2 years. From then onward, results from twice-a-year testing were similar to results from examinations scheduled 3 times per year. CONCLUSIONS: Irregular visual field test frequency at relatively short intervals initially and longer intervals later on in the disease provided acceptable results in detecting glaucoma progression. This approach could be considered for improving glaucoma monitoring. Moreover, simulating data using LMM may provide a better estimate of the disease progression time.

Pointwise and Region-Wise Course of Visual Field Loss in Patients With Glaucoma.

Purpose: Accurate assessment of visual field (VF) trend may help clinicians devise the optimum treatment regimen. This study was conducted to investigate the behavior of VF sequences using pointwise and region-wise linear, exponential, and sigmoid regression models. Materials and Methods: In a retrospective cohort study, 277 eyes of 139 patients with glaucoma who had been followed for at least 7 years were investigated. Linear, exponential, and sigmoid regression models were fitted for each VF test location and Glaucoma Hemifield Test (GHT) region to model the trend of VF loss. The model with the lowest root mean square error (RMSE) was selected as the best fit. Results: The mean age (standard deviation [SD]) of the patients was 59.9 years (9.8) with a mean follow-up time of 9.3 (0.7) years. The exponential regression had the best fit based on pointwise and region-wise approaches in 39.3% and 38.1% of eyes, respectively. The results showed a better performance based on sigmoid regression in patients with initial VF sensitivity threshold greater than 22 dB (71.6% in pointwise and 62.2% in region-wise approaches). The overall RMSE of the region-wise regression model was lower than the overall RMSE of the pointwise model. Conclusions: In the current study, nonlinear regression models showed a better fit compared to the linear regression models in tracking VF loss behavior. Moreover, findings suggest region-wise analysis may provide a more appropriate approach for assessing VF deterioration. Translational Relevance: Findings may confirm a nonlinear progression of VF deterioration in patients with glaucoma.

Prognosis and Long-Term Overall Survival in Hypertensive Patients Undergoing Chronic Hemodialysis: A Multicenter Parametric Mixture Split-Population Analysis.

BACKGROUND: Hemodialysis (HD) patients face long-term complications which require ongoing dialysis and follow-up. The management of hypertension among HD populations has often been neglected. This study aimed at identifying the determinants of death in hypertensive HD (HTN-HD) patients. METHODS: In a multicenter retrospective cohort study (conducted from 2005 to 2018 in thirty-four HD centers affiliated with Shiraz University of Medical Sciences), the data of 725 HTN-HD patients who had at least 3 months of regular dialysis and follow-up were analyzed. Accelerated failure time mixture split-population (AFTMSP) regression was utilized to identify the factors with significant effects on long- and short-term overall survival (OS) separately. RESULTS: Among the different AFTMSP models, the extended generalized gamma (EGG) model outperformed the others. Sex (male: event time ratio [ETR]=1.30), initial vascular access type (arteriovenous fistula: ETR=1.50), and the type of membrane flux used for HD (high-flux: ETR=1.27) had important impacts on short-term OS. Moreover, age (OR=1.06), dialysis adequacy (Kt/ Vurea≤1.2: OR=2.30), initial vascular access type (central venous catheter: OR=2.08), serum sodium (OR=0.90) concentration, and potassium (OR=0.66) concentration had significant effects on long-term OS. CONCLUSION: The split-population analyses were able to demonstrate that the predictors of long-term OS were different from those of short-term OS. Although the superiority of the parametric EGG model was proved in this study, further research with different databases is suggested. Moreover, these findings can be considered by health policy decision-makers to create a new guideline to enhance the long-term OS of HTN-HD patients.